Merge pull request aws#42 from awslabs/image_classification_notebooks

Synced image classification notebooks based on bash

Author: gurumurthys

introduction_to_amazon_algorithms/README.md

@@ -11,3 +11,4 @@ Example Notebooks include:
 - *seq2seq*: Seq2Seq algorithm is built on top of [Sockeye](https://github.com/awslabs/sockeye), a sequence-to-sequence framework for Neural Machine Translation based on MXNet. SageMaker Seq2Seq implements state-of-the-art encoder-decoder architectures which can also be used for tasks like Abstractive Summarization in addition to Machine Translation.
 - *xgboost_abalone*: Predicts the age of abalone ([Abalone dataset](https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/regression.html)) using regression from Amazon SageMaker XGBoost.
 - *xgboost_mnist*: Uses Amazon SageMaker XGBoost to classifiy handwritten digits from the MNIST dataset into one of the ten digits using a multi-class classifier. Both single machine and distributed use-cases are presented.
+- *image_classification*: Uses Amazon SageMaker Image classification algorithm to train a Resnet on [caltech dataset](http://www.vision.caltech.edu/Image_Datasets/Caltech256/), either from scratch or using a pre-trained model.